New Tesla Cybertruck window test video shows the glass doesn’t shatter
Tesla has released a slow motion video to prove that the Cybertruck’s “armour glass” works. So what went wrong?
by Joshua Dowling- shares
Tesla boss Elon Musk has released via social media a video showing the Cybertruck’s side glass can withstand a strike from a metal ball, after two windows shattered during an embarrassing demonstration at the vehicle’s unveiling in Los Angeles.
Musk was left red faced after a stunt to demonstrate the strength of the Tesla Cybertruck’s “armour glass” failed not once but twice in front of a live global audience.
Minutes after mocking the toughness of mainstream pick-ups such as the Ford F-150, Chevrolet Silverado, and Ram 1500, Musk had an offsider take a swing at the Tesla Cybertruck’s stainless steel door panels and then throw a metal ball – a bit bigger than a golf ball – at the driver’s door window.
However the stunt backfired when the glass shattered, which prompted Musk to say under his breath: “Oh my f- - - king god”.
To try to prove how strong the glass was a second time, the metal ball was thrown at the rear window, but that shattered too.
Musk looked genuinely stunned that the glass had broken, given that the test had worked in the lead-up to the event, he said, claiming the design team even threw a “kitchen sink” at it.
Less than 24 hours after the launch of the Tesla Cybertruck, Musk released a slow motion video of the same test in which the glass did not break.
Musk initially thought the ball may have been thrown with too much force during the on-stage demonstration, however another theory has since emerged.
Some experts believe the test of the glass immediately before the global unveiling of the Tesla Cybertruck may have created a micro-fracture, and the strike on stage may have been enough to break it.
However, that doesn’t explain why the rear glass shattered as well. It is unclear if Tesla had tested the steel ball on the rear glass prior to the stage show.
Appearing at times nervous, Musk then began explaining the Tesla Cybertruck’s features as he stood awkwardly in front of the two pieces of shattered glass.
Musk later said: “Oh well, a little room for improvement … it’s a little weird it broke now. (In testing) we threw everything at it, including a kitchen sink. At least it didn’t go through.”
In the 48 hours since the launch of the Tesla Cybertruck, which was unveiled Thursday evening in Los Angeles, motoring fans around the world are still trying to figure out if it’s real or not, and what design changes might be necessary before the vehicle hits the road.
While the triangular shape makes the Tesla Cybertruck look like something out of a science fiction movie, experts are wondering if its sharp lines would pass pedestrian safety tests and if the sleek headlights and taillights – and lack of bumpers – meet regulations.
It has also been noted there is no Tesla badging on the vehicle and the only colour available is the silver/grey stainless steel finish of the show car.
It has also since become apparent why the rear of the vehicle tapers the way it does: the sloping flat cover for the ute tray is more aerodynamic than an open cargo box.
Some pundits have speculated the Cybertruck’s unveiling was a stunt to raise more money for the firm.
However, despite the oddball looks and bold claims, Tesla insists the Cybertruck is real and coming to US showrooms in the next two years or so.
There are still no plans announced for Australia. Tesla is yet to reveal if the Cybertruck will be made in right-hand-drive.
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New Tesla Cybertruck window test video shows the glass doesn’t shatter


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|
OCILIB (C and C++ Driver for Oracle)
4.5.1
|
Object identifying the SQL data type LOB (CLOB, NCLOB and BLOB) More...
#include <ocilib.hpp>
Inherits ocilib::HandleHolder< OCI_Lob *>.
Public Member Functions | |
| Lob () | |
| Create an empty null Lob instance. | |
| Lob (const Connection &connection) | |
| Parametrized constructor. More... | |
| T | Read (unsigned int length) |
| Read a portion of a lob. More... | |
| unsigned int | Write (const T &content) |
| Write the given content at the current position within the lob. More... | |
| unsigned int | Append (const T &content) |
| Append the given content to the lob. More... | |
| void | Append (const Lob &other) |
| Append the given lob content to the lob. More... | |
| bool | Seek (SeekMode seekMode, big_uint offset) |
| Move the current position within the lob for read/write operations. More... | |
| LobType | GetType () const |
| return the type of lob | |
| big_uint | GetOffset () const |
| Returns the current R/W offset within the lob. | |
| big_uint | GetLength () const |
| Returns the number of characters or bytes contained in the lob. | |
| big_uint | GetMaxSize () const |
| Returns the lob maximum possible size. | |
| big_uint | GetChunkSize () const |
| Returns the current lob chunk size. More... | |
| Connection | GetConnection () const |
| Return the lob parent connection. | |
| void | Truncate (big_uint length) |
| Truncate the lob to a shorter length. More... | |
| big_uint | Erase (big_uint offset, big_uint length) |
| Erase a portion of the lob at a given position. More... | |
| void | Copy (Lob &dest, big_uint offset, big_uint offsetDest, big_uint length) const |
| Copy the given portion of the lob content to another one. More... | |
| bool | IsTemporary () const |
| Check if the given lob is a temporary lob. | |
| void | Open (OpenMode mode) |
| Open explicitly a Lob. More... | |
| void | Flush () |
| Flush the lob content to the server (if applicable) | |
| void | Close () |
| Close explicitly a Lob. More... | |
| void | EnableBuffering (bool value) |
| Enable / disable buffering mode on the given lob object. More... | |
| Lob | Clone () const |
| Clone the current instance to a new one performing deep copy. | |
| Lob & | operator+= (const Lob &other) |
| Appending the given lob content to the current lob content. | |
| bool | operator== (const Lob &other) const |
| Indicates if the current lob value is equal to the given lob value. | |
| bool | operator!= (const Lob &other) const |
| Indicates if the current lob value is not equal the given lob value. | |
Object identifying the SQL data type LOB (CLOB, NCLOB and BLOB)
This class wraps the OCILIB object handle OCI_Lob and its related methods
Definition at line 4077 of file ocilib.hpp.
| ocilib::Lob< T, U >::Lob | ( | const Connection & | connection | ) |
Parametrized constructor.
| connection | - Parent connection |
Definition at line 3000 of file ocilib_impl.hpp.
References ocilib::Check(), ocilib::Lob< T, U >::Lob(), ocilib::MakeRaw(), ocilib::MakeString(), OCI_LobCreate(), OCI_LobFree(), OCI_LobRead(), and ocilib::Lob< T, U >::Read().
| T ocilib::Lob< T, U >::Read | ( | unsigned int | length | ) |
Read a portion of a lob.
| length | - Maximum number of characters or bytes to read |
Referenced by ocilib::Lob< T, U >::Lob().
| unsigned int ocilib::Lob< T, U >::Write | ( | const T & | content | ) |
Write the given content at the current position within the lob.
| content | - content to write |
Definition at line 3042 of file ocilib_impl.hpp.
References ocilib::Check(), and OCI_LobWrite().
| unsigned int ocilib::Lob< T, U >::Append | ( | const T & | content | ) |
Append the given content to the lob.
| content | - content to write |
Definition at line 3061 of file ocilib_impl.hpp.
References ocilib::Check(), and OCI_LobAppend().
| void ocilib::Lob< T, U >::Append | ( | const Lob< T, U > & | other | ) |
Append the given lob content to the lob.
| other | - source lob |
Definition at line 3055 of file ocilib_impl.hpp.
References ocilib::Check(), and OCI_LobAppendLob().
| bool ocilib::Lob< T, U >::Seek | ( | SeekMode | seekMode, |
| big_uint | offset | ||
| ) |
Move the current position within the lob for read/write operations.
| seekMode | - Seek mode |
| offset | - offset from current position |
Definition at line 3074 of file ocilib_impl.hpp.
References ocilib::Check(), and OCI_LobSeek().
| big_uint ocilib::Lob< T, U >::GetChunkSize | ( | ) | const |
Returns the current lob chunk size.
Definition at line 3120 of file ocilib_impl.hpp.
References ocilib::Check(), and OCI_LobGetChunkSize().
| void ocilib::Lob< T, U >::Truncate | ( | big_uint | length | ) |
Truncate the lob to a shorter length.
| length | - New length in characters or bytes |
Definition at line 3132 of file ocilib_impl.hpp.
References ocilib::Check(), and OCI_LobTruncate().
| big_uint ocilib::Lob< T, U >::Erase | ( | big_uint | offset, |
| big_uint | length | ||
| ) |
Erase a portion of the lob at a given position.
| offset | - Absolute position in source lob |
| length | - Number of bytes or characters to erase |
Definition at line 3138 of file ocilib_impl.hpp.
References ocilib::Check(), and OCI_LobErase().
| void ocilib::Lob< T, U >::Copy | ( | Lob< T, U > & | dest, |
| big_uint | offset, | ||
| big_uint | offsetDest, | ||
| big_uint | length | ||
| ) | const |
Copy the given portion of the lob content to another one.
| dest | - Destination lob |
| offset | - Absolute position in the lob |
| offsetDest | - Absolute position in the destination lob |
| length | - Number of characters or bytes to copy |
Definition at line 3144 of file ocilib_impl.hpp.
References ocilib::Check(), and OCI_LobCopy().
| void ocilib::Lob< T, U >::Open | ( | OpenMode | mode | ) |
Open explicitly a Lob.
| mode | - open mode |
Definition at line 3156 of file ocilib_impl.hpp.
References ocilib::Check(), and OCI_LobOpen().
| void ocilib::Lob< T, U >::Close | ( | ) |
Close explicitly a Lob.
Definition at line 3168 of file ocilib_impl.hpp.
References ocilib::Check(), and OCI_LobClose().
| void ocilib::Lob< T, U >::EnableBuffering | ( | bool | value | ) |
Enable / disable buffering mode on the given lob object.
| value | - Enable/disable buffering mode |
Definition at line 3174 of file ocilib_impl.hpp.
References ocilib::Check(), and OCI_LobEnableBuffering().


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22 August 1894: Founded the 'Natal Indian Congress'.
11 October 1899: Established Indian Ambulance Corp during the Boer War.
1908: The term 'Satyagraha' adopted based on Maganlal Gandhi's fomulation 'Sadagraha'.
10 January 1908: Awarded two months' simple imprisonment for refusal to obtain registration.
13-22 November 1909: Wrote 'Hind Swarajya' aboard the ship 'Kildonan Castle'.
20 May 1915: Established 'Satyagraha Ashram', Kochrab.
19 November 1946: Handed over the responsibility of Harijan Journ2 June 1947als to Kaka Kalelkar, Kishorelal Mashruwala and Narahari Parikh.
2 June 1947: The Congress, the Muslim League and the representatives of the Sikhs accept the plan of Partition.
"
If we could change ourselves, the tendencies in the world would also change. As a man changes his own nature, so does the attitude of the world change towards him. We need not wait to see what others do."
--- Mahatma Gandhi


Top: Networking: ipstmserver
#include <pinet.h> class ipstmserver { ipstmserver(); int bind(ipaddress ip, int port); int bindall(int port); bool poll(int bindnum = -1, int timeout = 0); bool serve(ipstream& client, int bindnum = -1, int timeout = -1); }
The ipstmserver class is used on the server side of a stream-oriented client-server application. It bounds itself to a specified port/address and waits until a connection request is received from a client host. For each connection request a server application performs some actions and returns to the waiting state. For better performance your daemon may start a new thread for each client connection.
Ipstmserver can generate exceptions of type (estream*) with a corresponding error code and a message string.
ipstmserver::ipstmserver() constructs an ipstmserver object.
int ipstmserver::bind(ipaddress ip, int port) binds the server to the specified local IP address and port number. This function can be called multiple times for different local addresses and port numbers. Bind() returns a value that can be used later in call to poll() and serve() as the parameter bindnum.
int ipstmserver::bindall(int port) binds the server to all local IP address on the specified port number. Can be called multiple times for different port numbers. Bindall() returns a value that can be used later in call to poll() and serve() as the parameter bindnum.
bool ipstmserver::poll(int bindnum = -1, int timeout = 0) polls the listening sockets for connection requests. Bindnum specifies the socket number reutrned by bind() or bindall(). If bindnum is -1 poll() tests all sockets. The second parameter timeout specifies the amount of time in milliseconds to wait for a connection request. If timeout is 0 poll() returns immediately; if it's -1 poll() waits infinitely. This function returns true if there is a new connection request waiting for processing.
bool ipstmserver::serve(ipstream& client, int bindnum = -1, int timeout = -1) polls the specified bound sockets for connection requests. If there is a connection request, serve() opens and prepares the supplied ipstream object for communicating with the client, i.e. client will be active upon return from serve() and will contain the peer IP address and the port number. The meanings of bindnum and timeout are the same as for poll() except that the default value for timeout in this case is -1, i.e. wait infinitely. This function returns true if there is a new connection request and client is active, or false if the call has timed out.
See also: ipstream, Utilities, Examples


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java.lang.Object | +--org.apache.commons.lang.time.DateFormatUtils
Date and time formatting utilities and constants.
Formatting is performed using the
FastDateFormat
class.
| Field Summary | |
static FastDateFormat |
ISO_DATE_FORMAT
ISO8601 formatter for date without time zone. |
static FastDateFormat |
ISO_DATE_TIME_ZONE_FORMAT
ISO8601-like formatter for date with time zone. |
static FastDateFormat |
ISO_DATETIME_FORMAT
ISO8601 formatter for date-time without time zone. |
static FastDateFormat |
ISO_DATETIME_TIME_ZONE_FORMAT
ISO8601 formatter for date-time with time zone. |
static FastDateFormat |
ISO_TIME_FORMAT
ISO8601 formatter for time without time zone. |
static FastDateFormat |
ISO_TIME_NO_T_FORMAT
ISO8601-like formatter for time without time zone. |
static FastDateFormat |
ISO_TIME_NO_T_TIME_ZONE_FORMAT
ISO8601-like formatter for time with time zone. |
static FastDateFormat |
ISO_TIME_TIME_ZONE_FORMAT
ISO8601 formatter for time with time zone. |
static FastDateFormat |
SMTP_DATETIME_FORMAT
SMTP (and probably other) date headers. |
| Constructor Summary | |
DateFormatUtils()
DateFormatUtils instances should NOT be constructed in standard programming. |
| Method Summary | |
static String |
format(Date date,
String pattern)
Format a date/time into a specific pattern. |
static String |
format(Date date,
String pattern,
Locale locale)
Format a date/time into a specific pattern in a locale. |
static String |
format(Date date,
String pattern,
TimeZone timeZone)
Format a date/time into a specific pattern in a time zone. |
static String |
format(Date date,
String pattern,
TimeZone timeZone,
Locale locale)
Format a date/time into a specific pattern in a time zone and locale. |
static String |
format(long millis,
String pattern)
Format a date/time into a specific pattern. |
static String |
format(long millis,
String pattern,
Locale locale)
Format a date/time into a specific pattern in a locale. |
static String |
format(long millis,
String pattern,
TimeZone timeZone)
Format a date/time into a specific pattern in a time zone. |
static String |
format(long millis,
String pattern,
TimeZone timeZone,
Locale locale)
Format a date/time into a specific pattern in a time zone and locale. |
static String |
formatUTC(Date date,
String pattern)
Format a date/time into a specific pattern using the UTC time zone. |
static String |
formatUTC(Date date,
String pattern,
Locale locale)
Format a date/time into a specific pattern using the UTC time zone. |
static String |
formatUTC(long millis,
String pattern)
Format a date/time into a specific pattern using the UTC time zone. |
static String |
formatUTC(long millis,
String pattern,
Locale locale)
Format a date/time into a specific pattern using the UTC time zone. |
| Methods inherited from class java.lang.Object |
clone,
equals,
finalize,
getClass,
hashCode,
notify,
notifyAll,
toString,
wait,
wait,
wait |
| Field Detail |
public static final FastDateFormat ISO_DATETIME_FORMAT
public static final FastDateFormat ISO_DATETIME_TIME_ZONE_FORMAT
public static final FastDateFormat ISO_DATE_FORMAT
public static final FastDateFormat ISO_DATE_TIME_ZONE_FORMAT
public static final FastDateFormat ISO_TIME_FORMAT
public static final FastDateFormat ISO_TIME_TIME_ZONE_FORMAT
public static final FastDateFormat ISO_TIME_NO_T_FORMAT
public static final FastDateFormat ISO_TIME_NO_T_TIME_ZONE_FORMAT
public static final FastDateFormat SMTP_DATETIME_FORMAT
| Constructor Detail |
public DateFormatUtils()
DateFormatUtils instances should NOT be constructed in standard programming.
This constructor is public to permit tools that require a JavaBean instance to operate.
| Method Detail |
public static String formatUTC(long millis, String pattern)
Format a date/time into a specific pattern using the UTC time zone.
millis
- the date to format expressed in millisecondspattern
- the pattern to use to format the datepublic static String formatUTC(Date date, String pattern)
Format a date/time into a specific pattern using the UTC time zone.
date
- the date to formatpattern
- the pattern to use to format the datepublic static String formatUTC(long millis, String pattern, Locale locale)
Format a date/time into a specific pattern using the UTC time zone.
millis
- the date to format expressed in millisecondspattern
- the pattern to use to format the datelocale
- the locale to use, may be null
public static String formatUTC(Date date, String pattern, Locale locale)
Format a date/time into a specific pattern using the UTC time zone.
date
- the date to formatpattern
- the pattern to use to format the datelocale
- the locale to use, may be null
public static String format(long millis, String pattern)
Format a date/time into a specific pattern.
millis
- the date to format expressed in millisecondspattern
- the pattern to use to format the datepublic static String format(Date date, String pattern)
Format a date/time into a specific pattern.
date
- the date to formatpattern
- the pattern to use to format the datepublic static String format(long millis, String pattern, TimeZone timeZone)
Format a date/time into a specific pattern in a time zone.
millis
- the time expressed in millisecondspattern
- the pattern to use to format the datetimeZone
- the time zone to use, may be null
public static String format(Date date, String pattern, TimeZone timeZone)
Format a date/time into a specific pattern in a time zone.
date
- the date to formatpattern
- the pattern to use to format the datetimeZone
- the time zone to use, may be null
public static String format(long millis, String pattern, Locale locale)
Format a date/time into a specific pattern in a locale.
millis
- the date to format expressed in millisecondspattern
- the pattern to use to format the datelocale
- the locale to use, may be null
public static String format(Date date, String pattern, Locale locale)
Format a date/time into a specific pattern in a locale.
date
- the date to formatpattern
- the pattern to use to format the datelocale
- the locale to use, may be null
public static String format(long millis, String pattern, TimeZone timeZone, Locale locale)
Format a date/time into a specific pattern in a time zone and locale.
millis
- the date to format expressed in millisecondspattern
- the pattern to use to format the datetimeZone
- the time zone to use, may be null
locale
- the locale to use, may be null
public static String format(Date date, String pattern, TimeZone timeZone, Locale locale)
Format a date/time into a specific pattern in a time zone and locale.
date
- the date to formatpattern
- the pattern to use to format the datetimeZone
- the time zone to use, may be null
locale
- the locale to use, may be null
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Docstring:
Usage: qiime quality-control evaluate-composition [OPTIONS]
This visualizer compares the feature composition of pairs of observed and
expected samples containing the same sample ID in two separate feature
tables. Typically, feature composition will consist of taxonomy
classifications or other semicolon-delimited feature annotations. Taxon
accuracy rate, taxon detection rate, and linear regression scores between
expected and observed observations are calculated at each semicolon-
delimited rank, and plots of per-level accuracy and observation
correlations are plotted. A histogram of distance between false positive
observations and the nearest expected feature is also generated, where
distance equals the number of rank differences between the observed
feature and the nearest common lineage in the expected feature. This
visualizer is most suitable for testing per-run data quality on sequencing
runs that contain mock communities or other samples with known
composition. Also suitable for sanity checks of bioinformatics pipeline
performance.
Inputs:
--i-expected-features ARTIFACT FeatureTable[RelativeFrequency]
Expected feature compositions [required]
--i-observed-features ARTIFACT FeatureTable[RelativeFrequency]
Observed feature compositions [required]
Parameters:
--p-depth INTEGER Maximum depth of semicolon-delimited taxonomic ranks
to test (e.g., 1 = root, 7 = species for the greengenes
reference sequence database). [default: 7]
--p-palette TEXT Choices('Set1', 'Set2', 'Set3', 'Pastel1', 'Pastel2',
'Paired', 'Accent', 'Dark2', 'tab10', 'tab20', 'tab20b', 'tab20c',
'viridis', 'plasma', 'inferno', 'magma', 'terrain', 'rainbow')
Color palette to utilize for plotting.
[default: 'Set1']
--p-plot-tar / --p-no-plot-tar
Plot taxon accuracy rate (TAR) on score plot. TAR is
the number of true positive features divided by the
total number of observed features (TAR = true positives
/ (true positives + false positives)). [default: True]
--p-plot-tdr / --p-no-plot-tdr
Plot taxon detection rate (TDR) on score plot. TDR is
the number of true positive features divided by the
total number of expected features (TDR = true positives
/ (true positives + false negatives)). [default: True]
--p-plot-r-value / --p-no-plot-r-value
Plot expected vs. observed linear regression r value
on score plot. [default: False]
--p-plot-r-squared / --p-no-plot-r-squared
Plot expected vs. observed linear regression r-squared
value on score plot. [default: True]
--p-plot-bray-curtis / --p-no-plot-bray-curtis
Plot expected vs. observed Bray-Curtis dissimilarity
scores on score plot. [default: False]
--p-plot-jaccard / --p-no-plot-jaccard
Plot expected vs. observed Jaccard distances scores on
score plot. [default: False]
--p-plot-observed-features / --p-no-plot-observed-features
Plot observed features count on score plot.
[default: False]
--p-plot-observed-features-ratio / --p-no-plot-observed-features-ratio
Plot ratio of observed:expected features on score
plot. [default: True]
--m-metadata-file METADATA
--m-metadata-column COLUMN MetadataColumn[Categorical]
Optional sample metadata that maps observed-features
sample IDs to expected-features sample IDs. [optional]
Outputs:
--o-visualization VISUALIZATION
[required]
Miscellaneous:
--output-dir PATH Output unspecified results to a directory
--verbose / --quiet Display verbose output to stdout and/or stderr during
execution of this action. Or silence output if
execution is successful (silence is golden).
--citations Show citations and exit.
--help Show this message and exit.
Import:
from qiime2.plugins.quality_control.visualizers import evaluate_composition
Docstring:
Evaluate expected vs. observed taxonomic composition of samples
This visualizer compares the feature composition of pairs of observed and
expected samples containing the same sample ID in two separate feature
tables. Typically, feature composition will consist of taxonomy
classifications or other semicolon-delimited feature annotations. Taxon
accuracy rate, taxon detection rate, and linear regression scores between
expected and observed observations are calculated at each semicolon-
delimited rank, and plots of per-level accuracy and observation
correlations are plotted. A histogram of distance between false positive
observations and the nearest expected feature is also generated, where
distance equals the number of rank differences between the observed feature
and the nearest common lineage in the expected feature. This visualizer is
most suitable for testing per-run data quality on sequencing runs that
contain mock communities or other samples with known composition. Also
suitable for sanity checks of bioinformatics pipeline performance.
Parameters
----------
expected_features : FeatureTable[RelativeFrequency]
Expected feature compositions
observed_features : FeatureTable[RelativeFrequency]
Observed feature compositions
depth : Int, optional
Maximum depth of semicolon-delimited taxonomic ranks to test (e.g., 1 =
root, 7 = species for the greengenes reference sequence database).
palette : Str % Choices('Set1', 'Set2', 'Set3', 'Pastel1', 'Pastel2', 'Paired', 'Accent', 'Dark2', 'tab10', 'tab20', 'tab20b', 'tab20c', 'viridis', 'plasma', 'inferno', 'magma', 'terrain', 'rainbow'), optional
Color palette to utilize for plotting.
plot_tar : Bool, optional
Plot taxon accuracy rate (TAR) on score plot. TAR is the number of true
positive features divided by the total number of observed features (TAR
= true positives / (true positives + false positives)).
plot_tdr : Bool, optional
Plot taxon detection rate (TDR) on score plot. TDR is the number of
true positive features divided by the total number of expected features
(TDR = true positives / (true positives + false negatives)).
plot_r_value : Bool, optional
Plot expected vs. observed linear regression r value on score plot.
plot_r_squared : Bool, optional
Plot expected vs. observed linear regression r-squared value on score
plot.
plot_bray_curtis : Bool, optional
Plot expected vs. observed Bray-Curtis dissimilarity scores on score
plot.
plot_jaccard : Bool, optional
Plot expected vs. observed Jaccard distances scores on score plot.
plot_observed_features : Bool, optional
Plot observed features count on score plot.
plot_observed_features_ratio : Bool, optional
Plot ratio of observed:expected features on score plot.
metadata : MetadataColumn[Categorical], optional
Optional sample metadata that maps observed_features sample IDs to
expected_features sample IDs.
Returns
-------
visualization : Visualization


 Keep reading to see all that awaits you on the Red Planet.
Every 2 years, when Earth and Mars are closest to each other, the voyage to the fourth planet takes a brisk 9 months.
Aside from warm clothes, there are a few essentials you’ll want to bring from home: like a space suit, solar phone charger, sextant, and a good book
This browser does not support the video element.
This browser does not support the video element.
There’s a whole planet to explore, and we want to make sure you see the best parts. First among them is the beautiful rift valley, Valles Marineris.
This is one activity you won’t want to miss. For a small upgrade fee, you and your family can take a guided tour of Mars from the comfort of our all-terrain Rovers.
This browser does not support the video element.


IntroductionCredit: Jeremy Hylton, Google, Inc. The recipes in this chapter describe simple techniques for using Python in distributed systems. Programming distributed systems is a difficult challenge, and recipes alone won't even come close to completely solving it. The recipes help you get programs on different computers talking to each other, so that you can start writing applications. Remote Procedure Call (RPC) is an attractive approach to structuring a distributed system. The details of network communication are exposed through an interface that looks like normal procedure calls. When you call a function on a remote server, the RPC system is responsible for all the details of communication. It encodes the arguments so they can be passed over the network to the server, which might use different internal representations for the data. It invokes the right function on the remote machine and waits for a response. The recipes in this chapter use three different systems that provide RPC interfacesCommon Object Request Broker Architecture (CORBA), Twisted's Perspective Broker (PB), and, in most recipes, XML-RPC. These systems are attractive because they make it easy to connect programs that can be running on different computers and might even be written in different languages. CORBA is a rather "heavyweight" protocol, very rich in functionality, with specialized and dedicated marshaling and transport layers (and much more besides). XML-RPC is a lightweight, simple-to-use protocol, which uses XML to marshal the call and its associated data, and HTTP for transport. Being simple and lightweight, XML-RPC is less functionally rich than CORBA. Both CORBA and XML-RPC are well-established standards, with implementations available for a wide variety of languages. In particular, XML-RPC is so simple and widespread that XML-RPC recipes take up half this chapter, a good, if rough, indication of how often Pythonistas are using it in preference to other distributed programming approaches. PB is also "lightweight", while offering richer functionality than XML-RPC. However, PB is not a separate standard but a part of the Twisted framework, so PB implementations are currently limited to what Twisted itself provides and are mostly in Python. Perspective Broker is unusual among RPC systems because it openly exposes at application level the fact that network transactions are asynchronous, not synchronous like procedure calls within a single process. Therefore, in PB, the launching of a call to the remote procedure does not necessarily imply an immediate wait for the procedure's results; rather, the "result"s arrive "later" through a callback mechanism (specifically, Twisted's deferred objects). This asynchronous approach, which is the conceptual core of the Twisted framework, offers substantial advantages in terms of performance and scalability of the "result"ing network applications, but it may take some getting used to. Simon Foster's approach, shown in recipe, Recipe 15.7, is a simple way to get started exploring Perspective Broker. XML-RPC is well supported by the Python Standard Library, with the xmlrpclib module for writing XML-RPC clients and the SimpleXMLRPCServer module for writing XML-RPC servers. For Twisted, CORBA, and other RPC standards yet (such as the emerging SOAPSimple Object Access Protocolsystem), you need to install third-party extensions before you can get started. The recipes in this chapter include pointers to the software you need. Unfortunately, you will not find pointers specifically to SOAP resources for Python in the recipes: for such pointers, I suggest you check out http://pywebsvcs.sourceforge.net/. The Python Standard Library also provides a set of modules for doing the lower-level work of network programmingsocket, select, asyncore, and asynchat. The library also includes modules for marshaling data and sending it across sockets: struct, pickle, xdrlib. Chapter 13, includes recipes in which some of these modules are directly used, and Chapter 7, contains recipes dealing with serialization and marshaling. These lower-level modules, in turn, provide the plumbing for many other higher-level modules that directly support a variety of standard network protocols. Jeff Bauer offers Recipe 15.9, using the telnetlib module to send commands to remote machines via the Telnet protocol. Telnet is not a very secure protocol, and thus, except for use within well-protected LANs, has been largely supplanted by more secure protocols such as SSH (Secure Shell). Peter Cogolo and Anna Martelli Ravenscroft offer similar functionality to Bauer's, in Recipe 15.10, which uses SSH (via the third-party package paramiko) rather than Telnet. Six of the recipes, just about half of the chapter, focus on XML-RPC. Rael Dornfest and Jeremy Hylton demonstrate how to write an XML-RPC client program that retrieves data from O'Reilly's Meerkat service. Recipe 15.1 is only three lines long (including the import statement): indeed, this extreme conciseness is the recipe's main appeal. Brian Quinlan and Jeff Bauer contribute two different recipes for constructing XML-RPC servers. Quinlan, in Recipe 15.2, shows how to use the SimpleXMLRPCServer module from the Python Standard Library to handle incoming requests. Bauer's is Recipe 15.3. Medusa, like Twisted, is a framework for writing asynchronous network programs. In both cases, the libraries do most of the work; other than a few lines of initialization and registration, the server looks like normal Python code. Christop Dietze (with contributions from Brian Quinlan and Jeff Bauer), in Recipe 15.4, elaborates on the XML-RPC server theme by showing how to add the ability that enables remote clients to terminate the server cleanly. Rune Hansen, in Recipe 15.5, shows how to add several minor but useful niceties to your XML-RPC servers. Peter Arwanitis, in Recipe 15.6, demonstrates how to implement an XML-RPC server with Twisted and, at the same time, give your server a GUI, thanks to the wxPython GUI framework. A strong alternative to XML-based protocols is CORBA, an object-based RPC mechanism using its own protocol, IIOP (Internet Inter-Orb Protocol). CORBA is a mature technology compared to XML-RPC (or, even more, SOAP, which isn't used in any of these recipesapparently, Pythonistas aren't doing all that much with SOAP yet). CORBA was introduced in 1991. The Python language binding was officially approved more recently, in February 2000, and several ORBs (Object Request Brokersroughly, CORBA servers) support Python. Duncan Grisby, a researcher at AT&T Laboratories in Cambridge (U.K.), describes the basics of getting a CORBA client and server running in Recipe 15.8, which uses omniORB, a free ORB, and the Python binding he wrote for it. CORBA has a reputation for complexity, but Grisby's recipe makes it look straightforward. More steps are involved in the CORBA client than in the XML-RPC client example, but they are not difficult. To connect an XML-RPC client to a server, you just need a URL. To connect a CORBA client to a server, you need a URLa special corbaloc URLand you also need to know the server's interface. Of course, you need to know the interface regardless of protocol, but CORBA uses it explicitly. In general, CORBA offers more features than other distributed programming frameworksinterfaces, type checking, passing references to objects, and more. CORBA also supports just about every Python data type as argument or result. Regardless of the protocols or systems you choose, the recipes in this chapter can help get you started. Inter-program communication is an important part of building a distributed system, but it's just one part. Once you have a client and server working, you'll find you have to deal with other interesting, challenging problemserror detection, concurrency, and security, to name a few. The recipes here won't solve those problems, but they will prevent you from getting caught up in unimportant details of the communication protocols. Rob Riggs in Recipe 15.11 presents a simple way to use HTTPS (as supported by the Python Standard Library module httplib) to authenticate SSL clients; Simon Foster's previously mentioned Perspective Broker recipe provides a way to implement one specific but frequent strategy for error detection and handling, namely periodically trying to reconnect to a server after a timeout or explicitly discovered network error. |


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FileIndex Class
Definition at line
19
of
FileIndex.hpp
Member Functions
void
AddFile
(int32_t fileIndex,
Module
* module)
void
Write
(BinaryWriter& writer)
Member Variables
std::unordered_map<int32_t, std::string>
fileMap
std::mutex
mtx
Member Function Details
AddFile Member Function
void
cmajor::symbols::FileIndex::AddFile(int32_t fileIndex,
Module
* module)
Definition at line
13
of
FileIndex.cpp
Declaration at line
22
of
FileIndex.hpp
Calls:
cmajor::symbols::Module::GetFilePath
Write Member Function
void
cmajor::symbols::FileIndex::Write(BinaryWriter& writer)
Definition at line
28
of
FileIndex.cpp
:
29
{
30
cmajor
::
debug
::
WriteNumberOfFileIndexRecords
(
writer
,
fileMap
.
size
(
)
)
;
31
for
(
const
auto
&
p
:
fileMap
)
32
{
33
cmajor
::
debug
::
WriteFileIndexRecord
(
writer
,
p
.
first
,
p
.
second
)
;
34
}
35
}
Called by:
cmajor::symbols::Module::WriteProjectDebugInfoFile
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| Endpoint: | Method: | Query Parameters: | Description: |
|---|---|---|---|
| /cryptocoins | GET | start, limit, convert | Returns a paginated list of all active cryptocurrencies with latest market data. |
| /cryptocoins/:id | GET | Returns all static metadata available for the identified cryptocurrency. | |
| /usage | GET | Returns API key usage stats. |
*CORS-enabled endpoints with origin at https://leonardosposina.github.io
Important: This app instance will sleep after 30 minutes of inactivity.


Shivaji Maharaj is one of the great national heroes of India. He created an independent and sovereign state in Maharashtra which was based on justice, welfare of the people and tolerance to all faiths. The aims, objectives and Rajnitee of the Maratha Swaraj under Chhatrapati Shivaji provided a new direction to contemporary politics of India. In course of time, his movement assumed, the form of an all-India struggle; a struggle which was to change the political map of India. Shivaji Maharaj was born at the Shivneri fort near Junnar in Pune district on 19th February 1630. Shivaji’s mother, Jijabai was the daughter of Lakhuji Jadhavrao of Sindkhed. His father Shahajiraje Bhosale was a prominent sardar in the Deccan. At the time of Shivaji Maharaj’s birth, most of the territory in Maharashtra was under the possession of the Nizamshah of Ahmednagar and the Adilshah of Bijapur. In the coastal belt of Konkan there were two sea powers, the Portuguese and the Siddi. The British and the Dutch who were engaged in expanding their trade also had their factories on the coast. The Mughals, since the period of Emperor Akbar 1 wanted to expand their power in the South. The Mughals launched a campaign to conquer the Nizamshahi Kingdom. The Adilshah of Bijapur allied with the Mughals in this campaign. Shahahajiraje tried to save the Nizamshahi, but he could not withstand the combined might of the Mughals and the Adilshahi. The Nizamshahi kingdom came to an end in A.D. 1636. Thereafter Shahajiraje became a sardar of the Adilshah of Bijapur and was posted in Karnataka. The region comprising Pune, Supe, Indapur and Chakan parganas located between the Bhima and Nira rivers which was vested in Shahajiraje as a jagir was continued by the Adilshah. Shahaijiraje was also assigned a jagir of Banglore. Veermata Jijabai and Shivajiraje, stayed for a few years with Shahajiraje at Banglore till Shivajiraje was twelve years old. Shahajiraje entrusted the administration of the Pune jagir to Shivajiraje and Veermata Jijabai. Shivajiraje grew up amidst the hills and valleys of Pune region under the guidance of his mother Jijabai.
Lorem ipsum dolor sit amet, consectetur adipiscing elit.
ABC P.O. Box 283 8562 Fusce Rd. Mumbai India 400 028<PHONE_NUMBER>


Beautiful Artworks on Instagram by Creative Mints
by Paul0v2
We have yet another instagram post, this time is an amazing artist & designer from Czech Republic who loves to share his works and process on instagram. Take a look at these amazing painting & Drawings and let us know what you think.
For more from Creative Mints visit his Instagram instagram.com/emotionslive and art.creativemints.com.
My name is Mike, I'm 30, living and working in Prague, Czech Republic. I've been interested in art and design since I was a kid and I've been always looking for a way to express the emotions and feelings that surround me. I'm most fascinated and inspired by Renaissance art but I like to explore different styles – from impressionism to abstract art. I've been experimenting more lately too, looking for fresh styles and trends – for me the path of an artist is one of constant search for something new


--- layout: page title: "By Topic" description: "looking for something specific?" header-img: "img/wall.JPG" ---


|
| | point () |
| | Empty constructor. More...
|
| |
| template<indexer sz> |
| | point (const fspoint< Type, indexer, sz > &p) |
| | Constructor from a g24_lib::fspoint . More...
|
| |
| | point (const indexer n) |
| | Construct with a specific size. More...
|
| |
| | point (const indexer n, const Type &a) |
| | Construct with n elements equal to a . More...
|
| |
| | point (const indexer n, const Type *a) |
| | Construct with an array of n elements. More...
|
| |
| | point (const point< Type, indexer > &p) |
| | Copy constructor. More...
|
| |
| | point (const std::vector< Type > &v) |
| |
| | point (point< Type, indexer > &&p) |
| | Move constructor. More...
|
| |
| | ~point () |
| |
| Type | angle (const point< Type, indexer > &p) const |
| | Calculates the angle between two vectors with the usual inner product. More...
|
| |
| void | assure_size (const indexer desired) |
| | Ensures the size of the vector is desired . More...
|
| |
| template<class stream > |
| void | binary_input (stream &s) |
| |
| template<class stream > |
| void | binary_output (stream &s) const |
| |
| Type | cosangle (const point< Type, indexer > &p) const |
| | Calculates the co-sine of the angle between two vectors with the usual inner product. More...
|
| |
| point< Type, indexer > | crossp (const point< Type, indexer > &v) const |
| | Returns the cross (vector) product of two vectors. More...
|
| |
| point | delete_from (const indexer where) const |
| | Returns a point with an element deleted from the position specified by where . The original point is unchanged. More...
|
| |
| Type | dotp (const point< Type, indexer > &v) const |
| | Returns the dot (scalar) product of two vectors. More...
|
| |
| point< Type, indexer > | element_divide (const point &p) const |
| | Performs element-wise division. More...
|
| |
| point< Type, indexer > | element_divide (const Type *a) const |
| | Performs element-wise division. More...
|
| |
| point< Type, indexer > | element_multiply (const point &p) const |
| | Performs element-wise multiplication. More...
|
| |
| point< Type, indexer > | element_multiply (const Type *a) const |
| | Performs element-wise multiplication. More...
|
| |
| Type *& | get_access_to_array () |
| | Gives direct access to the underlying array. More...
|
| |
| const Type * | get_access_to_array () const |
| | Gives direct access to the underlying array. More...
|
| |
| void | inc_with_wrap (point< Type, indexer > &limits, const indexer where=0, bool reverse=false, bool brk=false) |
| | Increments the elements of the point with limits and a carry to the next element. More...
|
| |
| Type | max () const |
| |
| Type | max (indexer &comp) const |
| |
| Type | min () const |
| |
| Type | min (indexer &comp) const |
| |
| Type | multiply_all () const |
| |
| point< Type, indexer > | normalize (const indexer k=std::numeric_limits< indexer >::max(), const double norm=1.0, const double p=2.0) const |
| | Returns a normalized vector. More...
|
| |
| bool | operator!= (const point &p) const |
| |
| Type & | operator() (const indexer i) |
| | Bounded access operator. More...
|
| |
| const Type & | operator() (const indexer i) const |
| | Bounded access operator. More...
|
| |
| CUDA_HOS_DEV std::enable_if< g24_lib::Definitions::elementwise_point_operators, point >::type | operator* (const point &b) const |
| | Element-wise multiplication. More...
|
| |
| point | operator* (const Type &a) const |
| | Multiplication by scalar. More...
|
| |
| point | operator+ (const point &p) const |
| |
| point | operator+ (const Type *const a) const |
| |
| point & | operator+= (const point &p) |
| |
| point & | operator+= (const Type *const a) |
| |
| point | operator- () const |
| |
| point | operator- (const point &p) const |
| |
| point | operator- (const Type *const a) const |
| |
| point & | operator-= (const point &p) |
| |
| point & | operator-= (const Type *const a) |
| |
| CUDA_HOS_DEV std::enable_if< g24_lib::Definitions::elementwise_point_operators, point >::type | operator/ (const point &b) const |
| | Element-wise division. More...
|
| |
| point | operator/ (const Type &a) const |
| | Division by scalar. More...
|
| |
| point | operator<< (const point &p) const |
| | Concatenates two point s. More...
|
| |
| point | operator<< (const Type &x) const |
| | Inserts a new value to the end of the point . More...
|
| |
| point & | operator= (const point &p) |
| |
| point & | operator= (point &&p) |
| |
| bool | operator== (const point &p) const |
| |
| point | operator>> (const indexer n) const |
| | Removes n elements from the point . More...
|
| |
| Type & | operator[] (const indexer i) |
| |
| const Type & | operator[] (const indexer i) const |
| |
| point< Type, indexer > | ortog (const point< Type, indexer > &p, const bool normal=false) const |
| | Computes the orthogonal part of one vector acoording to another. More...
|
| |
| point< Type, indexer > | project (const point< Type, indexer > &p, const bool normal=false) const |
| | Computes the projection of one vector acoording to another. More...
|
| |
| void | raw_print (std::ostream &s, bool print_size=true) const |
| | Prints a point to a stream as a series of objects. More...
|
| |
| void | raw_read (std::istream &s) |
| | Reads a point from a stream as a size followed by a series of objects. More...
|
| |
| void | raw_read (std::istream &s, const indexer num) |
| | Reads a point from a stream as a series of objects with a known size. More...
|
| |
| point< Type, indexer > | reverse (const bool actually_do=true) const |
| | Returns a point with the same elements, but in reverse order. More...
|
| |
| CUDA_HOS_DEV void | set_all (const Type &a) |
| | Sets all elements of the vector to a . More...
|
| |
| const indexer | size () const |
| |
| Type | square_norm2 () const |
| |
| Type | sum_all () const |
| |
| template<class stream > |
| void | textual_input (stream &s) |
| |
| template<class stream , class str = std::basic_string<typename stream::char_type>> |
| void | textual_output (stream &s, const str &separator=" ") const |
| |
|
| Type | angle (const point< Type, indexer > &v, const point< Type, indexer > &u) |
| | Calculates the angle between two vectors with the usual inner product. More...
|
| |
| Type | cosangle (const point< Type, indexer > &v, const point< Type, indexer > &u) |
| | Calculates the co-sine of the angle between two vectors with the usual inner product. More...
|
| |
| point< Type, indexer > | crossp (const point< Type, indexer > &u, const point< Type, indexer > &v) |
| | Returns the cross (vector) product of two vectors. More...
|
| |
| Type | dotp (const point< Type, indexer > &u, const point< Type, indexer > &v) |
| | Returns the dot (scalar) product of two vectors. More...
|
| |
| template<class A , class B , B > |
| class | fspoint |
| |
| point< Type, indexer > | operator* (const Type &a, const point< Type, indexer > &p) |
| | Multiplies a scalar by a vector, for ease of writing some equations. More...
|
| |
| std::ostream & | operator<< (std::ostream &s, const point< Type, indexer > &p) |
| |
| point< Type, indexer > | ortog (const point< Type, indexer > &a, const point< Type, indexer > &b, const bool normal=false) |
| | Computes the orthogonal part of one vector acoording to another. More...
|
| |
| point< Type, indexer > | project (const point< Type, indexer > &a, const point< Type, indexer > &b, const bool normal=false) |
| | Computes the projection of one vector acoording to another. More...
|
| |
template<class Type, class indexer = g24_lib::Definitions::default_unsigned_indexer>
class g24_lib::point< Type, indexer >
A dynamically sized array of type Type
. Mainly to be used as an N-dimensional vector in mathematical or physical contexts.
- Template Parameters
-
| Type | The type of the elements of the array. |
| indexer | The type that should be able to hold the size of the array. |
- Precondition
Type
should provide appropriate arithmetic operators if point
is to be used as a mathematical vector.
-
indexer
must satisfy the constraints placed on the choice of g24_lib::Definitions::default_unsigned_indexer.
- Deprecated:
- This class is more or less deprecated since its usefulness is limited. In most practical problems, the dimensions are fixed, dynamic allocations are slower and
CUDA
interoperatability is quite limited. However, compatibility with past projects requires it to remain here for the time being, at least.
Definition at line 48 of file point.h.


Given n non-negative integers representing an elevation map where the width of each bar is 1, compute how much water it is able to trap after raining.
For example,
For the input array [2, 0, 2], we can trap 2 units of water.
| |
| _ |
For the input array [3, 0, 0, 2, 0, 4].
|
| |
| | |
|_ _| _ |
we can trap 10 units of water.
First let's try to simplify the problem.
An element will only be able to store water if there are bars of higher height to the left and right of it.
Naive Approach
A naive approach would be to traverse the array for each element finding the elements with the highest high on the left and right.
We can then take the minimum of the two values and get the value of water stored at that element.
Time complexity of this solution is O(N^2)
Efficient Approach
A more efficient approach would be to compute the highest element on the left for all the elements and the highest element on the right for all the elements and store them.
This will bring down the complexity to O(N).
The above approach can be implemented as follows:


CouchQuery Class Reference
| Inherits from | CouchResource : RESTResource : NSObject |
| Declared in | CouchQuery.h |
Tasks
-
designDocument
The design document that contains this view.
property -
limit
The maximum number of rows to return. Default value is 0, meaning ‘unlimited’.
property -
skip
The number of initial rows to skip. Default value is 0.
propertyShould only be used with small values. For efficient paging, use startkey and limit.
-
descending
Should the rows be returned in descending key order? Default value is NO.
property -
startKey
If non-nil, the key value to start at.
property -
endKey
If non-nil, the key value to end after.
property -
startKeyDocID
If non-nil, the document ID to start at.
property(Useful if the view contains multiple identical keys, making .startKey ambiguous.)
-
endKeyDocID
If non-nil, the document ID to end at.
property(Useful if the view contains multiple identical keys, making .endKey ambiguous.)
-
stale
If set, allows faster results at the expense of returning possibly out-of-date data.
property -
keys
If non-nil, the query will fetch only the rows with the given keys.
property -
groupLevel
If non-zero, enables grouping of results, in views that have reduce functions.
property -
prefetch
If set to YES, the results will include the entire document contents of the associated rows.
propertyThese can be accessed via CouchQueryRow's -documentProperties property. This can be a good optimization if you know you'll need the entire contents of each document. (This property is equivalent to "include_docs" in the CouchDB API.)
-
sequences
property -
includeDeleted
If set to YES, deleted documents are included in a getAllDocuments query.
propertyThis has NO EFFECT in view queries, and it's only supported on TouchDB, not CouchDB.
-
error
If non-nil, the error of the last execution of the query.
propertyIf nil, the last exexution of the query was successful
-
– start
Starts an asynchronous query of the CouchDB view.
When complete, the operation's resultObject will be the CouchQueryEnumerator.
-
– rows
Sends the query to the server and returns an enumerator over the result rows (Synchronous).
-
– rowsIfChanged
Same as rows, except returns nil if the query results have not changed since the last time it was evaluated (Synchronous).
-
– asLiveQuery
Returns a live query with the same parameters.
Properties
descending
Should the rows be returned in descending key order? Default value is NO.
@property BOOL descending
Discussion
Should the rows be returned in descending key order? Default value is NO.
Declared In
CouchQuery.h
designDocument
The design document that contains this view.
@property (readonly) CouchDesignDocument *designDocument
Discussion
The design document that contains this view.
Declared In
CouchQuery.h
endKey
If non-nil, the key value to end after.
@property (copy) id endKey
Discussion
If non-nil, the key value to end after.
Declared In
CouchQuery.h
endKeyDocID
If non-nil, the document ID to end at.
(Useful if the view contains multiple identical keys, making .endKey ambiguous.)
@property (copy) NSString *endKeyDocID
Discussion
If non-nil, the document ID to end at.
(Useful if the view contains multiple identical keys, making .endKey ambiguous.)
Declared In
CouchQuery.h
error
If non-nil, the error of the last execution of the query.
If nil, the last exexution of the query was successful
@property (readonly, retain) NSError *error
Discussion
If non-nil, the error of the last execution of the query.
If nil, the last exexution of the query was successful
Declared In
CouchQuery.h
groupLevel
If non-zero, enables grouping of results, in views that have reduce functions.
@property NSUInteger groupLevel
Discussion
If non-zero, enables grouping of results, in views that have reduce functions.
Declared In
CouchQuery.h
includeDeleted
If set to YES, deleted documents are included in a getAllDocuments query.
This has NO EFFECT in view queries, and it's only supported on TouchDB, not CouchDB.
@property BOOL includeDeleted
Discussion
If set to YES, deleted documents are included in a getAllDocuments query.
This has NO EFFECT in view queries, and it's only supported on TouchDB, not CouchDB.
Declared In
CouchQuery.h
keys
If non-nil, the query will fetch only the rows with the given keys.
@property (copy) NSArray *keys
Discussion
If non-nil, the query will fetch only the rows with the given keys.
Declared In
CouchQuery.h
limit
The maximum number of rows to return. Default value is 0, meaning ‘unlimited’.
@property NSUInteger limit
Discussion
The maximum number of rows to return. Default value is 0, meaning ‘unlimited’.
Declared In
CouchQuery.h
prefetch
If set to YES, the results will include the entire document contents of the associated rows.
These can be accessed via CouchQueryRow's -documentProperties property.
This can be a good optimization if you know you'll need the entire contents of each document.
(This property is equivalent to "include_docs" in the CouchDB API.)
@property BOOL prefetch
Discussion
If set to YES, the results will include the entire document contents of the associated rows.
These can be accessed via CouchQueryRow's -documentProperties property.
This can be a good optimization if you know you'll need the entire contents of each document.
(This property is equivalent to "include_docs" in the CouchDB API.)
Declared In
CouchQuery.h
skip
The number of initial rows to skip. Default value is 0.
Should only be used with small values. For efficient paging, use startkey and limit.
@property NSUInteger skip
Discussion
The number of initial rows to skip. Default value is 0.
Should only be used with small values. For efficient paging, use startkey and limit.
Declared In
CouchQuery.h
stale
If set, allows faster results at the expense of returning possibly out-of-date data.
@property CouchStaleness stale
Discussion
If set, allows faster results at the expense of returning possibly out-of-date data.
Declared In
CouchQuery.h
startKey
If non-nil, the key value to start at.
@property (copy) id startKey
Discussion
If non-nil, the key value to start at.
Declared In
CouchQuery.h
startKeyDocID
If non-nil, the document ID to start at.
(Useful if the view contains multiple identical keys, making .startKey ambiguous.)
@property (copy) NSString *startKeyDocID
Discussion
If non-nil, the document ID to start at.
(Useful if the view contains multiple identical keys, making .startKey ambiguous.)
Declared In
CouchQuery.h
Instance Methods
asLiveQuery
Returns a live query with the same parameters.
- (CouchLiveQuery *)asLiveQuery
Discussion
Returns a live query with the same parameters.
Declared In
CouchQuery.h
rows
Sends the query to the server and returns an enumerator over the result rows (Synchronous).
- (CouchQueryEnumerator *)rows
Discussion
Sends the query to the server and returns an enumerator over the result rows (Synchronous).
Declared In
CouchQuery.h
rowsIfChanged
Same as rows, except returns nil if the query results have not changed since the last time it was evaluated (Synchronous).
- (CouchQueryEnumerator *)rowsIfChanged
Discussion
Same as rows, except returns nil if the query results have not changed since the last time it was evaluated (Synchronous).
Declared In
CouchQuery.h
start
Starts an asynchronous query of the CouchDB view.
When complete, the operation's resultObject will be the CouchQueryEnumerator.
- (RESTOperation *)start
Discussion
Starts an asynchronous query of the CouchDB view.
When complete, the operation's resultObject will be the CouchQueryEnumerator.
Declared In
CouchQuery.h


Data Fields | |
| struct win_window * | container |
| Container, ultimate widget parent. | |
| char * | caption |
| Copy of caption string. | |
| bool | selected |
| True if selected. | |
| enum wtk_check_box_state | state |
| Current state. | |
| win_command_t | command |
| Command to send. Must be non-zero to be enabled. |
This is the check box control struct. It contains references to the windows composing the check box, as well as non-window information required.
Definition at line 68 of file wtk_check_box.c.
| char* wtk_check_box::caption |
Copy of caption string.
Definition at line 72 of file wtk_check_box.c.
Referenced by wtk_check_box_create(), and wtk_check_box_handler().
Command to send. Must be non-zero to be enabled.
Definition at line 78 of file wtk_check_box.c.
Referenced by wtk_check_box_create(), and wtk_check_box_handler().
| struct win_window* wtk_check_box::container |
Container, ultimate widget parent.
Definition at line 70 of file wtk_check_box.c.
Referenced by wtk_check_box_as_child(), wtk_check_box_create(), wtk_check_box_handler(), wtk_check_box_set(), and wtk_check_box_toggle().
True if selected.
Definition at line 74 of file wtk_check_box.c.
Referenced by wtk_check_box_create(), wtk_check_box_handler(), wtk_check_box_is_selected(), wtk_check_box_set(), and wtk_check_box_toggle().
Current state.
Definition at line 76 of file wtk_check_box.c.
Referenced by wtk_check_box_create(), and wtk_check_box_handler().


Behind the donut
Jam Donut Games is the development studio of hobbyist games developer Adam (Jam) Dougherty (Donut) a developer from the UK.
I've been developing software for 10 years professionally now but have never been a professional game developer. I enjoy making games in my spare time and hope to create a small niche for myself in the simulation market for desktop and mobile :P
In my About page I have tried to add details of the technical aspect of my games as well as personal opinions in order to allow other developers and creators to get a sense of the challenges involved in the project. Maybe there will be some take away for others.
Why do I make games?
For me, making a game is just as fun as playing a game. I also try to get in as much gaming time as I can since it's an amazing hobby to have.
Sometimes though, when no game is scratching the itch I just have to open my editor and code something, it's just like any creative or challenging game. Even making this webpage is part of that fun side of "making my own game".
That doesn't mean game development is just as easy as playing a game though... As a seasoned technical engineer I try my hardest to complete a personal project and take away from it anything that I can learn.
Some of my inspirations are obvious and I'm not shy about admitting it, Prison Architect and Rimworld are two amazing games which inspired the gameplay loop and art style of Arcade Builder. Reminds me of some saying about the sincerest form of flattery.
Aside from my influencers some other great games I love to play include Kerbal Space Program, Oxygen Not Included, Ark Survival Evolved and Kenshi. I highly recommend playing these games if you enjoy strategy or simulation!
Latest game showcase: Arcade Builder
Arcade Builder is a mobile, desktop and browser game built from the ground up as a solo project over a few years by myself.
It's a great little game that let's you:
- Build your own arcade business from the ground up.
- Hire and manage your staff
- Get hundreds of customers in your arcade
- Unlock research and find new suppliers
- Place loads of furniture and arcade machines
Creation
The development started out as a simple "I wonder if I could make a 'flatland' in javascript"... which lead on to realizing the game potential for what I was developing. Here's some footage on youtube from that version: https://www.youtube.com/watch?v=wyhPWiRk3Pc
After creating the demo previously shared I really wanted to make a game with what I had started. After staring at the screen and the little shapes walking around for a while it started to remind me of games I've played before... Prison Architect and Rimworld
With this in mind I came to realise a lot of the fundamentals that could go into making this game, such as the building of walls, placing of furniture, and staff/ai interacting with the furniture.
The idea for the game has evolved since day one, originally the game was going to be a hotel simulator but it just felt too obvious. In the end I decided to go with an Arcades Business simulator; inspired while on a trip to one of the arcades in my home town Blackpool. Now I had a game idea I wanted to go with...
The 'art'
When starting development on the game I had to face my fears of needing art for the game... In the past I have used mostly Pixel Art in my projects, but with this project I wanted to learn a new 'style' and so picked up Inkscape to do the art for the game. The overall goal was to get the art to look similar to other successful indie games, I'd say I got a solid 5/10 on that goal :P
With an understanding that my art wasn't going to be amazing I tried to ensure I would focus on the AI working, and having enough gameplay elements to make a fun game.
What about the code?
The games engine is developed in pure javascript using Notepad++. I do use IDE's and other tools in my work but for my hobbies I love using just a simple editor, sometimes I'll even write entire applications/chunks of code just in the chrome console
26k Lines of code excluding tooling/build scripts as of Jan 2020
Honest opinion: The code has it's upsides and it's downsides... the UI is a big mess of spaghetti and probably contributes to about 30% of the overall code (its just bad c+p code, trust me) but atleast I've controlled it by seperating code off into different files... The missions, research, upgrades all that is pretty basic but powerful so I like that. The saving system is quite good too.
The worst part to make: AI is just a pain.. Once you've nailed it you'll realise you're only 10% through the nightmare haha
I utilise a few Open Source projects that really enable the development of my games, these include:
Why not Unity/Unreal/Phaser etc?
My professional roles take me across several languages (PHP, Powershell, C#, JS) and my favourite was always JS... when HTML5 emerged years ago I decided I wanted to focus my efforts there only.
I have used HTML5 engines such as Phaser and Construct (AstroColonist & Attraction are both Construct 2) which are brilliant tools, but I always wanted to dig deeper into the code and how each individual "tick" was processed.
In the future I want to learn even more about the rendering layer, such as GPU rendering and Shaders.
Other Credits
As a solo developer I rely heavily on friends, family and open source and therefore I would like to credit the following for helping in all my projects.
- My parents
- Friends - Everyone who helps me test
- WensdiMade - For all sorts, no value can be placed on her contributions.
- Pash - For all sorts, no value can be placed on his contributions.
- Daniel Winfield - For patient testing and feedback
- PixiJS Contributors - If I didn't find this renderer, I wouldn't have had this much fun.
Tips for other creators
Some really simple tips that seem obvious but you have to keep reminding yourself... just keep going, set goals, make what you want to make...
If you stop for a while, that's fine just pick it back up again later, it'll feel nice and fresh in your mind when you come back to it.
Remake as you go. Especially true for UI, code and art. You might have made an art asset or a piece of code already, but I bet you could make it better a second time round or even the third time round... So if it ever comes down to improving something by replacing it, don't get precious about the thing you're throwing away. Life goes on.
Appreciate feedback, even the bad feedback. It'll be hard sometimes but even bad feedback is probably *real* feedback. You should seek feedback at every chance you get. My family and friends are probably sick of receiving 2-3 screenshots every day or so asking what they think. But it helps me and my project :)
Future
In the future I hope to release at least a couple more games on the same engine I've developed for Arcade Builder. I have a few ideas in the works such as a Casino building game, as well as potentially using the engine for more complex games, such as a survival builder or colony simulator.
Talk to me!
If you want to keep up to date with my development or give me feedback you can follow and tweet me on twitter @aJamDonut
If you like what I'm doing and want to chat please drop me a pm on twitter! If you want to join my community on discord then use the link here: Discord Server
TLDR
Some British Tea lover made a simulation game in Javascript that works on mobile, desktop and browser. He learnt a lot along the way, it was hard but fun and everyone lived happily ever after.
Other Games
I always endeavour to complete a game project even if it may mean there are certain shortcomings with gameplay, for this reason ofcourse the games are always free and available online:
You can check out some draft games and devlogs here: https://www.youtube.com/channel/UC5yH3WaxAWLYRVLIWveh7dg
Here are a selection of some of the games I've developed in the past!
Attraction - A short simplistic platformer where your arrow keys control two players at once.
AstroColonst - A 2D space RTS with planet management, alien attacks and RNG solar systems.
Arcade Builder Classic - The original release of Arcade Builder
World-Mafia - A multiplayer text-based mafia game with missions, heists and a great community


Import an existing website as a new realm
- sudo apt-get install httrack
- httrack -w http://foo.bar
- Add introspection link to (X)HTML head
- Make introspection documents available
- ...
- IMPORTANT: One might have to change the encoding:
iconv -f ISO-8859-1 -t UTF-8 page.html > page.html.UTF-8
(Please make sure that the meta content="application/xhtml+xml; charset=UTF-8" resp. the XML head encoding="UTF-8" is also being set appropriately. Also make sure that the server is sending the appropriate mime type which can be declared within the resource configuration .yanel-rc)


class: center, middle, inverse, title-slide # STA 235 - Causal Inference: Instrumental Variables ## Spring 2021 ### McCombs School of Business, UT Austin ---  # Introduction to instrumental variables .pull-left[ - We have seen that controlling for covariates is usually **.darkorange[not enough]**. - We might not have **.darkorange[randomization]** or **.darkorange[a nice RD]**. .box-7[What to do?] ] .pull-right[ .center[ ![](https://media.giphy.com/media/oGzFZek2lszlK/giphy.gif)] ] --- .center2[ .box-3[Instrumental variables could help!] -- .box-3t[... but first let's review some concepts.] ] --- # Endogeneity vs Exogeneity .center[Does education cause higher earnings?]  -- `$$\color{#F89441}{\text{Earnings}_i} = \beta_0 + \beta_1 \color{#900DA4}{\text{Education}_i} + \varepsilon_i$$` -- .box-4t[Would β1 give us the causal effect of Education on Earnings?] --- # Endogeneity vs Exogeneity .box-5[Endogenous variable] .center[*"A variable is said to be endogenous within the causal model M if its value is determined or influenced by one or more of the independent variables (excluding itself)." (Little, 2011)*] --

 .box-6[Exogenous variable] .center[*"An exogenous variable is a variable that is not affected by other variables in the system"*] --- # Back to earnings and education - **.darkorange[Education]** could be considered and *endogeneous* variable. - **.darkorange[Ability]** could be considered an *exogenous* variable.  --- # Can we do something about this? - We want some **.darkorange[exogeneous variation]** in education: - E.g. choices to get more or less education are essentially random (or unless uncorrelated with omitted variables) -- - We would like education to be **.darkorange[exogeneous]**, but it's not! Part of it is caused by **.darkorange[ability]** --

 .box-2[... but part of it is not. Can we separate both parts?] --- # Separate an edogenous variable $$ `\begin{aligned} \color{#FF851B}{\text{Earnings}_i} =& \beta_0 + \beta_1 \color{#B10DC9}{\text{Education}_i} + \varepsilon_i \\ & \beta_0 + \beta_1 (\color{#0074D9}{\text{Education}_i^\text{exog.}} + \color{#FF4136}{\text{Education}_i^\text{endog.}}) + \varepsilon_i \\ & \beta_0 + \beta_1 \color{#0074D9}{\text{Education}_i^\text{exog.}} + \underbrace{\beta_1 \color{#FF4136}{\text{Education}_i^{\text{endog.}}} + \varepsilon_i}_{\color{#AAAAAA}{\omega_i}} \\ & \beta_0 + \beta_1 \color{#0074D9}{\text{Education}_i^\text{exog.}} + \color{#AAAAAA}{\omega_i} \end{aligned}` $$ -- - How do we find `\(\text{Education}_i^{\text{exog}}\)`? --- # Instrumental variables to the rescue? .pull-left[ .center[ ![](https://media.giphy.com/media/LXRumZ7dCGBhvD9IyY/giphy.gif) ] ] .pull-right[ **.darkorange[Instrumental variables (IV)]** can help. - What is an IV? - Something that is correlated with the treatment: **.darkorange[Relevance]** - Something that does not directly cause the outcome: **.darkorange[Exclusion]** - Something that is not correlated with the ommited variables: **.darkorange[Exogeneity]** ] --- # Assumptions behind IVs .box-6[**.white[Relevance]**
Correlated with treatment] .box-6t[Z → D   Cor(Z, D) ≠ 0] --

 .box-7t[testable with stats] --- # Assumptions behind IVs .box-6[**.white[Exclusion]**
Correlated with outcome *only through* treatment] .box-6t[Z → D → Y   Z ↛ Y   Cor(Z, Y | D) = 0] --

 .box-7t[testable with stats + story] --- # Assumptions behind IVs .box-6[**.white[Exogeneity]**
*Not* correlated with omitted variables] .box-6t[U ↛ Z   Cor(Z, U) = 0] --

 .box-7t[Not testable with stats (only story!)] --- # Who do instruments work for? - When doing an IV analysis, we are only estimating an effect **.darkorange[for those who are moved by our instrument]**

 .box-2[Compliers] -- - We are not identifying and effect for "always-takers" or "never-takers" (also, we assume no defiers).

 .box-7[LATE] --- # Finding instruments is hard! - Usually the **.darkorange[exclusion restriction fails]**. -- - In the previous example of education, researchers have used **.darkorange[distance to college]** as an instrument. - **.darkorange[Is this valid?]** Why yes or why not? -- - However, good examples for an instrument could be treatment assignment in: .box-5[Fuzzy Regression Discontinuity Design]
 .box-5[Noncompliance in RCTs] --- # Two-stage least squares (2SLS) - **.darkorange[First stage]**: Regress endogenous variable (e.g. education) on instrument (e.g. distance to college), and get fitted values. `$$\widehat{\text{Education}}_i = \gamma_0 + \gamma_1\text{Distance}_i + \eta_i$$` -- - **.darkorange[Second stage]**: Regress outcome (e.g. income) on predicted values of endogenous variable (e.g. `\(\widehat{\text{Education}}_i\)`). `$$\text{income}_i = \beta_0 + \beta_1\widehat{\text{Education}}_i + \varepsilon_i$$` --- # Let's go back to GOTV example - RCT were households were randomized into GOTV calls. - We had random treatment assignment, but high noncompliance (e.g. people did not pick up their phone). --

 .box-2[What was the outcome of interest?] --
 .box-4[What is the endogenous variable?] --
 .box-7[What could be an instrument?] --- # GOTV compliance ```r d <- read.csv("https://raw.githubusercontent.com/maibennett/sta235/main/exampleSite/content/Classes/Week4/1_RCT/data/voters_covariates.csv") # Drop variables with unlisted phone numbers d_s1 <- d[!is.na(d$treat_real),] # Treatment assignment vs Actual treatment table(d_s1$treat_real, d_s1$contact) # % of treated by assignment d_s1 %>% group_by(treat_real) %>% summarise(contact = mean(contact)) ``` --- # GOTV compliance ```r d <- read.csv("https://raw.githubusercontent.com/maibennett/sta235/main/exampleSite/content/Classes/Week4/1_RCT/data/voters_covariates.csv") # Drop variables with unlisted phone numbers d_s1 <- d[!is.na(d$treat_real),] # Treatment assignment vs Actual treatment *table(d_s1$treat_real, d_s1$contact) # % of treated by assignment d_s1 %>% group_by(treat_real) %>% summarise(contact = mean(contact)) ``` .small[ ``` ## ## 0 1 ## 0 1845348 0 ## 1 34929 25043 ``` ] --- # GOTV compliance ```r d <- read.csv("https://raw.githubusercontent.com/maibennett/sta235/main/exampleSite/content/Classes/Week4/1_RCT/data/voters_covariates.csv") # Drop variables with unlisted phone numbers d_s1 <- d[!is.na(d$treat_real),] # Treatment assignment vs Actual treatment table(d_s1$treat_real, d_s1$contact) # % of treated by assignment *d_s1 %>% group_by(treat_real) %>% summarise(contact = mean(contact)) ``` .small[ ``` ## # A tibble: 2 x 2 ## treat_real contact ## <int> <dbl> ## 1 0 0 ## 2 1 0.418 ``` ] --- # GOTV: First stage ```r library(estimatr) *lm1 <- estimatr::lm_robust(contact ~ treat_real, data = d_s1) summary(lm1) ``` ``` ## ## Call: ## estimatr::lm_robust(formula = contact ~ treat_real, data = d_s1) ## ## Standard error type: HC2 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) CI Lower CI Upper DF ## (Intercept) 5.176e-13 8.601e-16 601.8 0 5.160e-13 5.193e-13 1905318 ## treat_real 4.176e-01 2.014e-03 207.4 0 4.136e-01 4.215e-01 1905318 ## ## Multiple R-squared: 0.4098 , Adjusted R-squared: 0.4098 ## F-statistic: 4.3e+04 on 1 and 1905318 DF, p-value: < 2.2e-16 ``` ```r d_s1$contact_fitted = lm1$fitted.values ``` --- # GOTV: First stage ```r library(estimatr) lm1 <- estimatr::lm_robust(contact ~ treat_real, data = d_s1) summary(lm1) ``` ``` ## ## Call: ## estimatr::lm_robust(formula = contact ~ treat_real, data = d_s1) ## ## Standard error type: HC2 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) CI Lower CI Upper DF ## (Intercept) 5.176e-13 8.601e-16 601.8 0 5.160e-13 5.193e-13 1905318 ## treat_real 4.176e-01 2.014e-03 207.4 0 4.136e-01 4.215e-01 1905318 ## ## Multiple R-squared: 0.4098 , Adjusted R-squared: 0.4098 ## F-statistic: 4.3e+04 on 1 and 1905318 DF, p-value: < 2.2e-16 ``` ```r *d_s1$contact_fitted = lm1$fitted.values ``` --- # GOTV: Second stage ```r *estimatr::lm_robust(vote02 ~ contact_fitted, data = d_s1) ``` ``` ## Estimate Std. Error t value Pr(>|t|) CI Lower ## (Intercept) 0.54528902 0.0003665575 1487.59488 0.000000e+00 0.54457058 ## contact_fitted 0.08728695 0.0049029128 17.80308 6.778072e-71 0.07767741 ## CI Upper DF ## (Intercept) 0.54600746 1905318 ## contact_fitted 0.09689648 1905318 ``` --- # GOTV: Intention to Treat ```r *lm2 <- estimatr::lm_robust(vote02 ~ treat_real, data = d_s1) summary(lm2) ``` ``` ## ## Call: ## estimatr::lm_robust(formula = vote02 ~ treat_real, data = d_s1) ## ## Standard error type: HC2 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) CI Lower CI Upper DF ## (Intercept) 0.54529 0.0003666 1487.6 0.000e+00 0.54457 0.54601 1905318 ## treat_real 0.03645 0.0020473 17.8 6.778e-71 0.03244 0.04046 1905318 ## ## Multiple R-squared: 0.0001634 , Adjusted R-squared: 0.0001629 ## F-statistic: 316.9 on 1 and 1905318 DF, p-value: < 2.2e-16 ``` ```r lm2$coefficients[2]/lm1$coefficients[2] ``` ``` ## treat_real ## 0.08728695 ``` --- # GOTV: Intention to Treat ```r lm2 <- estimatr::lm_robust(vote02 ~ treat_real, data = d_s1) summary(lm2) ``` ``` ## ## Call: ## estimatr::lm_robust(formula = vote02 ~ treat_real, data = d_s1) ## ## Standard error type: HC2 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) CI Lower CI Upper DF ## (Intercept) 0.54529 0.0003666 1487.6 0.000e+00 0.54457 0.54601 1905318 ## treat_real 0.03645 0.0020473 17.8 6.778e-71 0.03244 0.04046 1905318 ## ## Multiple R-squared: 0.0001634 , Adjusted R-squared: 0.0001629 ## F-statistic: 316.9 on 1 and 1905318 DF, p-value: < 2.2e-16 ``` ```r *lm2$coefficients[2]/lm1$coefficients[2] ``` ``` ## treat_real ## 0.08728695 ``` --- # GOTV: 2SLS - You can recover point estimates with the previous methods, but **.darkorange[standard errors will be wrong]** (unless you adjust them). -- - You can use packages designed for this, e.g. `ivreg` or `iv_robust()` from `estimatr` ```r summary(iv_robust(vote02 ~ contact | treat_real, data = d_s1)) ``` ``` ## ## Call: ## iv_robust(formula = vote02 ~ contact | treat_real, data = d_s1) ## ## Standard error type: HC2 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) CI Lower CI Upper DF ## (Intercept) 0.54529 0.0003666 1487.6 0.000e+00 0.54457 0.54601 1905318 ## contact 0.08729 0.0048760 17.9 1.166e-71 0.07773 0.09684 1905318 ## ## Multiple R-squared: 0.0005131 , Adjusted R-squared: 0.0005126 ## F-statistic: 320.5 on 1 and 1905318 DF, p-value: < 2.2e-16 ``` --- # Fuzzy Regression Discontinuity - The same principal applies when we **.darkorange[don't have full compliance]** in an RDD -- - **.darkorange[Fuzzy regression discontinuity]** - If `\(Z = I(R_i>c)\)`, then `\(\text{Pr}(D=1| Z=1)<1\)` and/or `\(\text{Pr}(D=1| Z=0)>0\)` -- ```r rdrobust(y = y, x = x, c = c, fuzzy = treat) ``` --- # Example: Entrance exam and tutoring  --- # Use above/below cutoff as instrument: A parametric approach .small[ ```r tutoring <- tutoring %>% mutate(distance = entrance_exam - 70, below_cutoff = entrance_exam <= 70) *summary(iv_robust(exit_exam ~ distance + tutoring | distance + below_cutoff, * data = filter(tutoring, distance >= -10 & distance <= 10))) ``` ``` ## ## Call: ## iv_robust(formula = exit_exam ~ distance + tutoring | distance + ## below_cutoff, data = filter(tutoring, distance >= -10 & distance <= ## 10)) ## ## Standard error type: HC2 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) CI Lower CI Upper DF ## (Intercept) 60.1414 1.0177 59.098 9.747e-200 58.1407 62.1420 400 ## distance 0.4366 0.0993 4.397 1.407e-05 0.2414 0.6318 400 ## tutoringTRUE 9.7410 1.9118 5.095 5.384e-07 5.9825 13.4996 400 ## ## Multiple R-squared: 0.3646 , Adjusted R-squared: 0.3615 ## F-statistic: 13.06 on 2 and 400 DF, p-value: 3.19e-06 ``` ] --- # Use above/below cutoff as instrument: A nonparametric approach .small[ ```r library(rdrobust) *summary(rdrobust(y = tutoring$exit_exam, x = tutoring$distance, c = 0, fuzzy = tutoring$tutoring)) ``` ``` ## Call: rdrobust ## ## Number of Obs. 1000 ## BW type mserd ## Kernel Triangular ## VCE method NN ## ## Number of Obs. 238 762 ## Eff. Number of Obs. 170 347 ## Order est. (p) 1 1 ## Order bias (q) 2 2 ## BW est. (h) 12.985 12.985 ## BW bias (b) 19.733 19.733 ## rho (h/b) 0.658 0.658 ## Unique Obs. 238 762 ## ## ============================================================================= ## Method Coef. Std. Err. z P>|z| [ 95% C.I. ] ## ============================================================================= ## Conventional 9.683 1.893 5.116 0.000 [5.973 , 13.393] ## Robust - - 4.258 0.000 [5.210 , 14.095] ## ============================================================================= ``` ] --- # Takeaways .pull-left[ - Instruments can be **.darkorange[useful]** for recovering treatment effects, even under no random assignment. - Finding good instruments is **.darkorange[hard]**. - We can easily use them in RCTs or RD designs to go **.darkorange[from an ITT to a LATE]**. ] .pull-right[ .center[ ![](https://media.giphy.com/media/WVAP0Z0Ue0UA64FNN7/giphy.gif) ] ] --- # References - Angrist, J. and S. Pischke. (2015). "Mastering Metrics". *Chapter 3*. - Heiss, A. (2020). "Program Evaluation for Public Policy". *Class 11: Instrumental Variables, Course at BYU*.


For those who aren't familiar with the ROV industry, ROV stands for Remotely Operated Vehicle. Almost always, an ROV is an underwater vehicle designed to complete tasks that are too dangerous, too boring, or too difficult for a human diver to accomplish. ROVs are piloted remotely with signals sent through a tether and have made it as deep as 35,000 feet below the sea floor. By percent growth, it is one of the fastest growing engineering industries. Other than this team, Purdue is currently taking no initiative on the subject while universities around the world are devoting entire majors to the subject (often referred to as 'Ocean Engineering').
The Purdue IEEE ROV team is dedicated to competing in the world's largest ROV competition, the MATE (Marine Advanced Technology Education Center) competition. The mission this year simulated underwater volcano study ROVs that can take temperature reading in multiple vents, collect unknown crustaceans for research inside of caves, collect a specific amount of sea-floor bacteria, and deploy long-term monitoring equipment in locations emitting a specific noise.
Including the entry level Ranger class and more technical Explorer class (Purdue competes in the Explorer class), there were over 400 team from around the world!
Purdue competed on June 25th at the University of Hawaii in Hilo and placed 4th overall internationally (after placing 5th internationally last year)! This put Purdue ahead of such universities as MIT, Georgia Tech, UNC, and Arizona State! The vehicle, ROV Competence, was a major step forward in technology and build quality from the 2009 vehicle, ROV Osprey. ROV Competence was the fastest vehicle at the competition with many unique features. However, the vehicle suffered from dual motor failure 5 seconds before the mission began after showing no signs of problems during the 100+ hours of practice. The issue was traced afterward to an underwater wire connection. Even with this handicap, the vehicle performed extremely well!
Thanks to all those at Purdue who have helped us get to where we are!
Purdue will be returning to next year's competition which will be at NASA's Neutral Buoyancy Lab in Houston, Texas. The lab is the largest indoor pool in the world with a depth of 40 feet!
We are still in desperate need of financial support and more than welcome suggestions for grants or sponsorships! Our limited funding for the 2010 competition forced us to leave half the team behind and spend more on travel than on the vehicle itself!
Please forward this to anyone you may think would be interested!
Thanks for your interest!
Seth Baklor
Team Captain
Junior, Industrial Engineering
I would like to thank you again for sponsoring the Purdue IEEE ROV Team.
The 2010 MATE ROV competition is now over. This was the second year for the team, and we have placed 4th overall internationally (an improvement from last year's 5th place finish). This put us ahead of many respected universities such as MIT, UNC, Arizona State, and Georgia Tech. We also placed ahead of teams from Russia, China, Iran, Scotland, and Canada.
ROV Competence would have easily secured a 2nd place finish; however, it suffered from a major failure. Immediately before the mission run which a perfect mission score was expected, ROV Competence lost one of its waterproof motor connections which took away one vertical and one horizontal motor (the first major failure to hit the vehicle in its over 100 hours of practice time). This made the vehicle extremely slow and hard to control. However it still scored extremely high with this handicap.
The team is already looking forward to the 2011 competition in Houston, Texas at NASA's Neutral Buoyancy Lab. This is the largest indoor pool in the world. While we do not know the mission yet, we do know that the vehicle will need to be designed for operation at 40 feet of depth. This poses many unique challenges that should make for an exciting build.
Please see attached for a photo of the ROV with all sponsors recognized with decals permanently attached to the vehicle. All sponsors were also recognized on our poster, technical report, and professional presentation.
We are always in need of more financial support and donations of parts/tools (including right now)!
Thanks Again,
Seth Baklor
Team Captain
Purdue University IEEE ROV Team
The Purdue IEEE ROV Team received 4th Place in the 2010 MATE (Marine Advanced Technology Education) Center International ROV Competition at the University of Hawaii - Hilo. The loss of one of the waterproof motor connections disabled a horizontal and a vertical thruster, but the team managed to complete the mission with the sluggish vehicle due to the experience afforded by 100+ hours of practice.
ROV Competence, the second vehicle created by the Purdue University IEEE ROV team, has been designed to accomplish and exceed the 2010 MATE International ROV Competition mission requirements. The vehicle is designed with a focus on reliability, handling, and dexterity. This focus stems from the challenges presented in this mission and in the history of volcano study. All of these goals were to be accomplished within a final vehicle cost of approximately $6,000 (not including the cost of research, testing, and transportation).
The vehicle is designed to deploy testing equipment near seismic activity, collect a sample of a new species of crustacean, test water temperature at multiple vent sites, and collect a specific sample size of bacterial mat. ROV Competence accomplishes all expected tasks in a single dive while remaining only 60cm long, 35cm wide, and 22cm tall.
More information about ROV Competence may be found in the technical report.
Pictures from this season may be found on Facebook. Press releases sent around Purdue and to team sponsors may be found in the two articles above. A video of the volcano study mission runs may be found on YouTube.


Version 2.0.1
Twitter Bootstrap is now just Bootstrap, and I’ve renamed this repo, renamed the files and change all references from Twitter Bootstrap to just Bootstrap in the docs/example to reflect that.
No actual code changed, so I am keeping the current version (2.0.1
at the time of this writing), but be aware of the lack of twitter- from the beginning of the JS files and how that might affect you.
Sorry for any inconvenience!
I updated the demo with Bootstrap 3, as well as removed code associated to submenus (not supported in Bootstrap 3) and touch devices (just make sure you have data-toggle="dropdown"
to let Mobile do its thing and my plugin won’t interfere).
A simple plugin to enable Bootstrap dropdowns to activate on hover and provide a nice user experience.
The dropdowns are dismissed after a configurable delay. This fixes an issue that can instantly close your nav because of a 1px gap between the button/nav item that activated the dropdown and the actual dropdown. It is also generally a better user experience, as users are not punished by going 1 pixel outside of the dropdown, which would instantly close the nav without a delay.
Note: The HTML markup is the same as with any other Bootstrap dropdown. This will not interfere with Bootstrap’s default activate-on-click method (i.e. this plugin combined with Bootstrap’s default behavior work well to support both the ideal experience on desktop and mobile).
You can simply download and extract the package downloaded from GitHub. Alternatively, you can download the files via Bower (a JavaScript package management system):
bower install bootstrap-hover-dropdown
which will also automatically install Bootstrap and jQuery if needed.
Once you have the files downloaded, link to the files in your code after you include the main Bootstrap JS file(s):
html

Just like in Bootstrap you can activate it without any JavaScript, just by adding a data-attribute, you can make it automatically work.
Add data-hover="dropdown"
in addition (or in place of) Bootstrap’s data-toggle="dropdown"
.
You can set options via data-attributes, too, via data-delay
and data-close-others
. Here’s an example of markup:
html

Account

My Account

Change Email

Change Password

Logout

Alternatively, you can initialize via JavaScript:
javascript
$('.dropdown-toggle').dropdownHover(options);
This also works with submenus without any other configuring since Bootstrap already supports this feature. Just use the markup like you were using before. Only the top level anchor tag needs any special markup for my plugin to work (see demo for proper markup).
500
.true
.You can view a demo for this plugin on my site: http://cameronspear.com/demos/bootstrap-hover-dropdown/
This plugin purposedly lets you choose a selector (as opposed to apply this to everything with the class of .dropdown-toggle
). This is so that you can selectively apply it where you want. Maybe you only want to use it for the main nav, and not have it activate for dropdown buttons in the main content. You can add a class to the item that normally gets .dropdown-toggle
and use that class with this plugin to easily achieve that, or use a selector such as .main-nav .dropdown-toggle
.
Important: Bootstrap relies on styles associated with the class .dropdown-toggle
(for stuff like the caret color), and it is recommended you leave that class alone.
I’m a slacker and only started keeping track of changes/bug fixes starting in March of 2013.
bootstrap-2.x.x
branch.instantlyCloseOthers
option, as it’s not really relevant.Mattia Larentis helped me with the idea for the data-attributes and doing the options via an object.
As this plugin, in its simplicity, is pretty much exactly what I intend it to be, I don’t plan to implement any new features. ~~One exception: I would like to tweak it so that when you’re in a submenu, it doesn’t instantly close when you hover outside of it.~~ Update: I added this in late April 2013.
If you have ideas for a new feature or something along those lines, you’re welcome to share them with me, but I am not likely to implement it/merge your pull without a very compelling reason. You are absolutely free to create a fork and implement the feature yourself for your and others’ use.
This, of course, does not speak for bugs. If you have a bug, please bring it to my attention, and I will try and fix it. Note that 93.7% of people’s issues are caused by incorrect markup, so please double check that first.


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| Cockpit Guide |
|---|
cockpit-bridgecockpit-bridge — Cockpit Host Bridge |
cockpit-bridge
[--help
] [--packages
]
The cockpit-bridge program is used by Cockpit to relay messages and commands from the Web front end to the server. Among other things it relays DBus, and spawns processes on behalf of the Web user interface.
This program is not routinely run by users or administrators. It
is in the $PATH
so that Cockpit can find it when connecting
between hosts. However there are some diagnostics available when running
from the command line.
|
Show help options. |
|
Interact with the raw cockpit1 protocol. Useful for debugging and testing.
Specify a |
|
List all available Cockpit packages and exit. Note this includes packages available to the user running this command. |


Deleting a Vendor Account
How to permanently delete a vendor account from the Vendors module.
- Locate the required vendor account.
- Click the Edit button beside the required vendor.
- Click the Delete button. This displays the message "Are You Sure You Wish To Delete This Item?"
-


Small (1.5 KB minified and gzipped) library for fuzzymatching strings
Performant up to ~10,000 items
Match results are memoized
Search against one or multiple lists at a time
Perfect for creating autocomplete widgets
Words
Search against a list of 10,000 common english words. The "score" you see is the internal score generated to sort results. It is the sum of the word's Levenshtein distance and the match position.
Cities of the world
Search against the 3531 cities in the world with a population over 100,000. City data is provided by geonames.org. Map images are provided by MapQuest using Open Street Maps.


Export Xpub
cfd0883d
********
m/48'/0'/0'/2'
View Seed Words
Export Xpub
Export Seed as QR
No option to add or edit passphrase.
Hide passphrase lock line entirely if no passphrase set.


Exodus 3:3
And Moses said, I will now turn aside, and see this great sight, why the bush is not burnt.


| 3594 - Quicksum North America - Mid Central - 2006/2007 | |||||
| Submit | Ranking |
A checksum is an algorithm that scans a packet of data and returns a single number. The idea is that if the packet is changed, the checksum will also change, so checksums are often used for detecting transmission errors, validating document contents, and in many other situations where it is necessary to detect undesirable changes in data.
For this problem, you will implement a checksum algorithm called Quicksum. A Quicksum packet allows only uppercase letters and spaces. It always begins and ends with an uppercase letter. Otherwise, spaces and letters can occur in any combination, including consecutive spaces.
A Quicksum is the sum of the products of each character's position in the packet times the character's value. A space has a value of zero, while letters have a value equal to their position in the alphabet. So, A=1, B=2, etc., through Z=26. Here are example Quicksum calculations for the packets ``ACM" and ``MID CENTRAL":
ACM:
1 * 1 + 2 * 3 + 3 * 13 = 46
MID CENTRAL:
1 * 13 + 2 * 9 + 3 * 4 + 4 * 0 + 5 * 3 + 6 * 5 + 7 * 14 + 8 * 20 + 9 * 18 + 10 * 1 + 11 * 12 = 650
The input consists of one or more packets followed by a line containing only # that signals the end of the input. Each packet is on a line by itself, does not begin or end with a space, and contains from 1 to 255 characters.
For each packet, output its Quicksum on a separate line in the output.
ACM MID CENTRAL REGIONAL PROGRAMMING CONTEST ACN A C M ABC BBC #
46 650 4690 49 75 14 15


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